xgb.plot.multi.trees: Project all trees on one tree and plot it

View source: R/xgb.plot.multi.trees.R

xgb.plot.multi.treesR Documentation

Project all trees on one tree and plot it


Visualization of the ensemble of trees as a single collective unit.


  feature_names = NULL,
  features_keep = 5,
  plot_width = NULL,
  plot_height = NULL,
  render = TRUE,



produced by the xgb.train function.


names of each feature as a character vector.


number of features to keep in each position of the multi trees.


width in pixels of the graph to produce


height in pixels of the graph to produce


a logical flag for whether the graph should be rendered (see Value).


currently not used


This function tries to capture the complexity of a gradient boosted tree model in a cohesive way by compressing an ensemble of trees into a single tree-graph representation. The goal is to improve the interpretability of a model generally seen as black box.

Note: this function is applicable to tree booster-based models only.

It takes advantage of the fact that the shape of a binary tree is only defined by its depth (therefore, in a boosting model, all trees have similar shape).

Moreover, the trees tend to reuse the same features.

The function projects each tree onto one, and keeps for each position the features_keep first features (based on the Gain per feature measure).

This function is inspired by this blog post: https://wellecks.wordpress.com/2015/02/21/peering-into-the-black-box-visualizing-lambdamart/


When render = TRUE: returns a rendered graph object which is an htmlwidget of class grViz. Similar to ggplot objects, it needs to be printed to see it when not running from command line.

When render = FALSE: silently returns a graph object which is of DiagrammeR's class dgr_graph. This could be useful if one wants to modify some of the graph attributes before rendering the graph with render_graph.


data(agaricus.train, package='xgboost')

bst <- xgboost(data = agaricus.train$data, label = agaricus.train$label, max_depth = 15,
               eta = 1, nthread = 2, nrounds = 30, objective = "binary:logistic",
               min_child_weight = 50, verbose = 0)

p <- xgb.plot.multi.trees(model = bst, features_keep = 3)

## Not run: 
# Below is an example of how to save this plot to a file.
# Note that for `export_graph` to work, the DiagrammeRsvg and rsvg packages must also be installed.
gr <- xgb.plot.multi.trees(model=bst, features_keep = 3, render=FALSE)
export_graph(gr, 'tree.pdf', width=1500, height=600)

## End(Not run)

xgboost documentation built on March 31, 2023, 10:05 p.m.